DO EMPLOYEES PROFIT FROM PROFIT SHARING? A LONGITUDINAL ANALYSIS OF CANADIAN ESTABLISHMENTS
Bibliographic record
Abstract
Using panel data from a large sample of Canadian establishments, this paper examines whether there is any link between adoption of an employee profit sharing plan and subsequent employee earnings. Overall, growth in employee earnings during the three-year period subsequent to adoption of profit sharing did not differ significantly between establishments that had or had not adopted profit sharing. However, growth in employee earnings was significantly higher among profit sharing adopters that paid above-market wages prior to adoption of profit sharing. This suggests that profit sharing may be financially beneficial to employees in establishments making high investments in human capital. Although employee profit sharing is a pay practice that has a long history (Coates, 1991), and one that many firms continue to adopt (Lawler, Mohrman, & Ledford, 1998; Long & Shields, 2005; Parent, 2002), there is little evidence on whether and under what conditions employees benefit financially from profit sharing. While proponents argue that profit sharing increases total employee earnings (Bell & Hanson, 1987; Tyson, 1996), others contend that the effect of profit sharing on
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".